Deep Learning Toolbox Model for GoogLeNet Network

Pretrained GoogLeNet network model for image classification

GoogLeNet is a pretrained model that has been trained on a subset of the ImageNet database which is used in the ImageNet Large-Scale Visual Recognition Challenge (ILSVRC). The model is trained on more than a million images, has 144 layers, and can classify images into 1000 object categories (e.g. keyboard, mouse, pencil, and many animals).

Opening the googlenet.mlpkginstall file from your operating system or from within MATLAB will initiate the installation process for the release you have.

This mlpkginstall file is functional for R2017b and beyond. Use googlenet instead of imagePretrainedNetwork if using a release prior to R2024a.

Usage Example:

% Access the trained model
[net, classes] = imagePretrainedNetwork("googlenet");

% See details of the architecture
net.Layers

% Read the image to classify
I = imread('peppers.png');

% Adjust size of the image
sz = net.Layers(1).InputSize
I = I(1:sz(1),1:sz(2),1:sz(3));

% Classify the image using GoogLeNet
scores = predict(net, single(I));
label = scores2label(scores, classes)

% Show the image and the classification results
figure
imshow(I)
text(10,20,char(label),'Color','white')